Reliability and Correlation with Quality of Life Outcomes of Unified Visual Function Scale
Bibliographic record
Abstract
Background Historically, descriptions of visual acuity and visual field change following intracranial procedures have been very rudimentary. Clinicians and researchers have often used basic descriptions such as “improved,” “worsened,” and “unchanged” to describe outcomes following resections of tumors affecting the optic apparatus. These descriptors are vague, difficult to quantify, and are challenging to apply in a clinical perspective. We present a novel way to describe a patient’s visual function as a combination of visual acuity and visual field assessment—Unified Visual Function Scale (UVFS). It is simple to use and can be used by surgeons, and researchers to gauge visual outcomes following tumor resection. Objective We combined visual acuity and visual fields into three categories designed around the definition of legal blindness and fitness to drive in Canada. We then tested for inter- and intraobserver reliabilities of the UVFS, and assessed whether UVFS scores reflect visual quality of life outcomes. Methods Six independent observers (two medical students, two neurosurgical trainees, and two neurosurgical staff members) were asked to assess visual acuity and visual fields and assign appropriate UVFS scores. These were then tested for inter- and intraobserver reliabilities. Additionally, Visual Function Questionnaire (VFQ-25) and Activities of Daily Vision Scale (AVDS) surveys were mailed out to 50 patients with previously treated perisellar meningiomas and results were analyzed against UVFS scores for correlation. Conclusion The UVFS is a robust way to assess a patient’s vision combining visual fields and acuity. We believe it is reliable when used by clinicians, and its implementation in a clinical setting is strengthened by reflection of patient visual quality of life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".